Belt fault detection method and device of clothes treatment equipment and clothes treatment equipment

Abstract

The invention provides a belt fault detection method and device for clothes processing equipment and the clothes processing equipment, and the method comprises the steps: determining a first starting moment of a fluctuation period of rotation of a roller according to first fluctuation data of motor operation; recording at least two first starting moments to form a first time sequence; according to the electrical angle data of the motor, the number of pole pairs of the motor and a set transmission ratio, estimating a second starting moment of the fluctuation period of roller rotation; recording at least two second starting moments to form a second time sequence; and determining whether the belt is in a fault state according to the first time sequence and the second time sequence. According to the belt fault detection method of the clothes processing equipment, whether the belt breaks down or not can be determined by collecting the operation data of the motor, and detection of the reliability of the belt is achieved.

Description

Technical Field

[0001] This invention relates to the field of garment processing equipment technology, and more specifically to a method, apparatus, and garment processing equipment for detecting belt failures in garment processing equipment. Background Technology

[0002] In related technologies, washing machines use belt drive to drive the drum via a motor. Belt drive requires a large amount of friction to ensure the transmission of force, so a large belt tension is usually required. However, during long-term use, the belt's friction decreases due to material aging, wear, and stretching, resulting in belt slippage. Currently, there is no effective way to detect belt slippage. Summary of the Invention

[0003] The present invention aims to at least solve or improve the technical problem in the prior art that it is impossible to detect whether the belt of the garment processing equipment is malfunctioning.

[0004] Therefore, the first aspect of the present invention proposes a method for detecting belt failure in a garment processing device.

[0005] A second aspect of the present invention provides a belt failure detection device for a garment processing equipment.

[0006] A third aspect of the present invention provides a garment processing device.

[0007] A fourth aspect of the present invention provides an electronic device.

[0008] A fifth aspect of the present invention provides a storage medium.

[0009] In view of the above, according to a first aspect of the present invention, the present invention provides a belt fault detection method for a garment processing equipment, comprising: determining a first start time of the fluctuation period of the roller rotation based on first fluctuation data of motor operation; recording at least two first start times to form a first time sequence; estimating a second start time of the fluctuation period of the roller rotation based on the electrical angle data of the motor, the number of pole pairs of the motor and a set transmission ratio; recording at least two second start times to form a second time sequence; and determining whether the belt is in a fault state based on the first time sequence and the second time sequence.

[0010] The present invention proposes a belt fault detection method for garment processing equipment. During operation, the garments inside the rollers cause uneven weight distribution, resulting in eccentric loads. Consequently, the rollers' rotation speed fluctuates. Based on the combination of the motor's control function and the eccentric load, the initial fluctuation data of the motor's operation exhibits a periodicity. Since the rollers are driven by the motor via a belt, the roller fluctuations are reflected in the initial fluctuation data of the motor according to the actual transmission ratio between the rollers and the motor. In other words, the fluctuation period of the roller rotation matches the initial fluctuation data of the motor.

[0011] As shown above, based on the first fluctuation data during motor operation, the first starting moment of the fluctuation cycle of the drum rotation is determined. Due to the eccentricity of the load inside the drum, the drum rotation speed will form a sine or cosine waveform based on the effect of gravity. Therefore, each fluctuation cycle of the drum rotation has a first starting moment. The first starting moments of at least two fluctuation cycles are determined and recorded to form a first time series. The first time series can reflect the actual transmission ratio between the drum and the motor.

[0012] The electrical angle data of the motor is acquired. Based on the electrical angle data, the number of motor pole pairs, and the set transmission ratio, the second starting time of the roller rotation fluctuation cycle is estimated. Each estimated roller rotation fluctuation cycle has a second starting time. The second starting times of at least two fluctuation cycles are determined and recorded to form a second time series. Since the single-turn rotation of the motor is not affected by the actual transmission ratio, the roller rotation fluctuation cycle under reliable belt conditions can be estimated using the electrical angle data, the number of motor pole pairs, and the predetermined transmission ratio. Therefore, the second time series can serve as standard data reflecting the predetermined transmission ratio. The electrical angle data can be converted into the motor rotation angle using the number of motor pole pairs.

[0013] As shown above, by using the first time series and the second time series, the actual transmission ratio between the roller and the motor can be determined, and whether it meets the predetermined transmission ratio, thereby determining whether the current belt is in a fault state.

[0014] In other words, by collecting motor operating data, this invention can determine whether the belt is faulty, thereby enabling belt reliability testing and reducing the possibility of overall machine failure due to belt failure in garment processing equipment.

[0015] In addition, the belt fault detection method for the garment processing equipment according to the above-described technical solution provided by the present invention may also have the following additional technical features:

[0016] In some embodiments, optionally, determining whether the belt is in a fault state based on a first time series and a second time series includes: comparing a first start time in the first time series with a second start time in the second time series of the same fluctuation period; and determining that the belt is in a fault state if a first difference between the first start time and the second start time is greater than or equal to a first threshold.

[0017] In this embodiment, determining whether the belt is in a fault state based on the first time series and the second time series includes: taking the first start time of a certain fluctuation period in the first time series, taking the second start time of the same fluctuation period in the second time series, subtracting the first start time and the second start time to obtain a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much larger than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, which can remind the user to repair or replace the belt, thereby reducing the impact of calculation error and detection error.

[0018] In some embodiments, optionally, comparing the first start time in the first time series of the same fluctuation period and the second start time in the second time series includes: when the motor is rotating at a constant speed, comparing the first start time in the first time series of the same fluctuation period and the second start time in the second time series; when the motor is rotating at an accelerated speed, comparing the first start time in the first time series of the fluctuation period when the speed drops back to the preset speed and the second start time in the second time series to determine whether the belt is in a fault state.

[0019] In this embodiment, comparing the first start time in the first time series with the second start time in the second time series of the same fluctuation period includes: when the motor is rotating at a constant speed, taking the first start time of a certain fluctuation period in the first time series, taking the second start time of the same fluctuation period in the second time series, subtracting the first start time from the second start time to obtain a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much greater than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, and reminding the user to repair or replace the belt.

[0020] When the motor is accelerating, the first and second starting times are recorded before the motor accelerates. After the motor completes the acceleration and the speed drops back to the preset speed, the first and second starting times are recorded again. When comparing, the first and second starting times after the speed drops back to the preset speed are compared. This can determine whether the belt drive is reliable when the motor is running at a high speed, and thus determine whether the belt is in a faulty state, thereby improving the reliability of belt fault diagnosis.

[0021] In some embodiments, optionally, determining the first start time of the fluctuation period of the drum rotation based on the first fluctuation data of the motor operation includes: determining the maximum fluctuation value of the rotation speed based on the first fluctuation data of the motor operation; adjusting the operating parameters of the motor when the maximum fluctuation value of the rotation speed is within a preset fluctuation value range; and determining the first start time of the fluctuation period of the drum rotation based on the first fluctuation data when the maximum fluctuation value of the rotation speed is outside the preset fluctuation value range.

[0022] In this embodiment, determining the first start time of the fluctuation cycle of the drum rotation based on the first fluctuation data of the motor operation includes: analyzing the first fluctuation data, extracting the maximum speed fluctuation value, and judging the maximum speed fluctuation value. If the maximum speed fluctuation value is outside the preset fluctuation value range, it indicates that the current load eccentricity of the drum is too large or too small, resulting in excessive or insufficient speed fluctuation, making it impossible to accurately determine the fluctuation cycle. In this case, the load eccentricity can be adjusted by adjusting the motor operating parameters until the maximum speed fluctuation value is within the preset fluctuation value range. Once the maximum speed fluctuation value is within the preset fluctuation value range, the determination of the first start time can begin, thereby improving the accuracy and reliability of the determination of the first start time.

[0023] In some embodiments, optionally, when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, determining the first starting time of the fluctuation period of the drum rotation based on the first fluctuation data includes: when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, determining the average rotational speed of the drum rotation based on the first fluctuation data; when the data point of the first fluctuation data and the average rotational speed are equal, and the rotational speed shows an upward trend, recording the time corresponding to the data point as the first starting time.

[0024] In this embodiment, when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, the first starting moment of the fluctuation period of the drum rotation is determined based on the first fluctuation data. This includes: when the maximum fluctuation value of the rotational speed is within the preset fluctuation value range, analyzing the first fluctuation data and determining the average rotational speed; if a certain data point of the first fluctuation data is equal to the average rotational speed, and the rotational speed at that data point shows an upward trend, the time corresponding to the data point is determined as the first starting moment, and this moment is recorded. Based on the characteristic of the load eccentricity inside the drum, when the drum rotates, its rotational speed changes from small to large and then from large to small. Therefore, by defining the position of the first starting moment in the above manner, the accuracy of determining the fluctuation period can be improved.

[0025] In some embodiments, optionally, estimating the second start time of the oscillation cycle of the drum rotation based on the electrical angle data of the motor, the number of motor pole pairs, and a set transmission ratio includes: calculating the electrical angle change of the motor based on the electrical angle data and the number of motor pole pairs; accumulating the electrical angle change to estimate the electrical angle change cycle that conforms to the oscillation cycle of the drum; determining that the electrical angle change cycle enters the next cycle when the electrical angle change cycle conforms to the set transmission ratio; and determining the second start time of the oscillation cycle of the drum rotation based on the electrical angle change cycle.

[0026] In this embodiment, estimating the second starting moment of the roller rotation fluctuation period based on the motor's electrical angle data, the number of motor pole pairs, and the set transmission ratio includes: calculating the change in the motor's electrical angle based on the motor's electrical angle data and the number of motor pole pairs. During the rotation of the motor, its electrical angle changes constantly. Combining this with the number of motor pole pairs, the change in electrical angle can be determined. The change in electrical angle reflects the number of rotations of the motor. When the belt drive is reliable, the number of rotations of the motor and the number of rotations of the roller should conform to the set transmission ratio of the belt. Therefore, the change in electrical angle that conforms to the roller's fluctuation period can be estimated by the change in electrical angle. In other words, the change in electrical angle is determined by accumulating the changes in electrical angle.

[0027] After confirming that the accumulated electrical angle change within the electrical angle change cycle meets the set transmission ratio, the electrical angle change cycle is determined to enter the next cycle, thus obtaining waveform data of one electrical angle change cycle. The starting time of the electrical angle change cycle is used as the second starting time, thereby improving the accuracy of the estimation of the roller's fluctuation cycle.

[0028] In some embodiments, the first start time and the second start time may be initialized simultaneously.

[0029] In this embodiment, the first start time and the second start time are initialized simultaneously, so that the first start time in the first time series and the second start time in the second time series correspond one-to-one, making it easier to compare the first start time and the second start time.

[0030] In some embodiments, the first fluctuation data may optionally be at least one of the following: speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data.

[0031] In this embodiment, the rotational speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data are all affected by the load inside the drum. Therefore, the oscillation period of the drum can be determined by analyzing the above data.

[0032] According to a second aspect of the present invention, a belt fault detection device for a garment processing equipment is provided, comprising: a first determining module, configured to determine a first starting moment of the fluctuation period of the roller rotation based on first fluctuation data of motor operation; a first recording module, configured to record at least two first starting moments to form a first time series; an estimation module, configured to estimate a second starting moment of the fluctuation period of the roller rotation based on the electrical angle data of the motor and a set transmission ratio; a second recording module, configured to record at least two second starting moments to form a second time series; and a second determining module, configured to determine whether the belt is in a fault state based on the first time series and the second time series.

[0033] The belt fault detection device for garment processing equipment proposed in this invention addresses the issue that during operation, the garments inside the rollers can cause uneven weight distribution, resulting in eccentric loads and fluctuations in the roller's rotation speed. Based on the combination of the motor's control function and the eccentric load, the initial fluctuation data of the motor's operation exhibits a periodicity. Since the roller is driven by the motor via a belt, the roller's fluctuations are reflected in the motor's initial fluctuation data according to the actual transmission ratio between the roller and the motor. In other words, the roller's rotational fluctuation period matches the motor's initial fluctuation data.

[0034] As shown above, based on the first fluctuation data during motor operation, the first starting moment of the fluctuation cycle of the drum rotation is determined. Due to the eccentricity of the load inside the drum, the drum rotation speed will form a sine or cosine waveform based on the effect of gravity. Therefore, each fluctuation cycle of the drum rotation has a first starting moment. The first starting moments of at least two fluctuation cycles are determined and recorded to form a first time series. The first time series can reflect the actual transmission ratio between the drum and the motor.

[0035] The electrical angle data of the motor is acquired. Based on the electrical angle data and the set transmission ratio, the second starting time of the fluctuation period of the roller rotation is estimated. Each fluctuation period of the roller rotation has a second starting time. The second starting times of at least two fluctuation periods are determined and recorded to form a second time series. Since the single-turn rotation of the motor is not affected by the actual transmission ratio, the fluctuation period of the roller rotation under the condition of reliable belt can be estimated by using the electrical angle data and the predetermined transmission ratio. Therefore, the second time series can be used as standard data reflecting the predetermined transmission ratio.

[0036] As shown above, by using the first time series and the second time series, the actual transmission ratio between the roller and the motor can be determined, and whether it meets the predetermined transmission ratio, thereby determining whether the current belt is in a fault state.

[0037] In other words, by collecting motor operating data, this invention can determine whether the belt is faulty, thereby enabling belt reliability testing and reducing the possibility of overall machine failure due to belt failure in garment processing equipment.

[0038] According to a third aspect of the present invention, a garment processing device is provided, including a controller for storing and running programs or instructions, which, when executed, implement the steps of the belt fault detection method for the garment processing device as described in the first aspect embodiment.

[0039] The garment processing device proposed in this invention includes a program or instructions that, when executed by a controller, implement the belt fault detection method for the garment processing device as proposed in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method for the garment processing device as proposed in the first aspect embodiment, which will not be described in detail here.

[0040] According to a fourth aspect of the present invention, an electronic device is provided, including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the belt fault detection method for a clothing processing device as proposed in the first aspect embodiment.

[0041] The electronic device proposed in this invention includes a program or instructions that, when executed by a processor, implement the belt fault detection method for the garment processing device as proposed in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method for the garment processing device as proposed in the first aspect embodiment, which will not be described in detail here.

[0042] According to a fifth aspect of the present invention, a storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the steps of the belt fault detection method for a garment processing device as described in the first aspect embodiment.

[0043] The storage medium proposed in this invention stores a computer program that, when executed by a processor, implements the steps of the belt fault detection method for the garment processing equipment as proposed in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method for the garment processing equipment as proposed in the first aspect embodiment, which will not be described in detail here.

[0044] Additional aspects and advantages of the invention will become apparent in the following description or may be learned by practice of the invention. Attached Figure Description

[0045] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0046] Figure 1 One of the flowcharts of a belt failure detection method for a garment processing device according to an embodiment of the present invention is shown;

[0047] Figure 2 A second flowchart of a belt fault detection method for a garment processing device according to an embodiment of the present invention is shown;

[0048] Figure 3 A schematic block diagram of the control object and transfer function of the motor speed control system in the belt fault detection method of the clothing processing equipment provided in an embodiment of the present invention is shown.

[0049] Figure 4 One of the diagrams showing the correspondence between the actual fluctuation period and the estimated fluctuation period of the roller in the belt fault detection method of the garment processing equipment provided in an embodiment of the present invention is illustrated.

[0050] Figure 5 The second diagram shows the correspondence between the actual fluctuation period and the estimated fluctuation period of the roller in the belt fault detection method of the clothing processing equipment provided in an embodiment of the present invention.

[0051] Figure 6 A structural block diagram of a belt fault detection device for a garment processing equipment according to an embodiment of the present invention is shown;

[0052] Figure 7 A structural block diagram of a garment processing device according to an embodiment of the present invention is shown;

[0053] Figure 8A schematic diagram of a portion of the structure of a garment processing device according to an embodiment of the present invention is shown;

[0054] Figure 9 A schematic diagram of a portion of the structure of a garment processing device provided in an embodiment of the present invention is shown.

[0055] in, Figure 8 and Figure 9 The correspondence between the reference numerals and component names in the attached drawings is as follows:

[0056] 810 Motor, 812 Motor Shaft, 820 First Pulley, 830 Second Pulley, 840 Roller, 850 Belt, 860 Load, 870 Support Pulley. Detailed Implementation

[0057] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0058] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0059] The following reference Figures 1 to 9 This invention describes a belt fault detection method, apparatus, and garment processing equipment for garment processing, provided by some embodiments of the present invention.

[0060] According to a first aspect of the present invention, the present invention provides a method for detecting belt failure in a garment processing device. Figure 1 A flowchart of a belt fault detection method for a garment processing device according to an embodiment of the present invention is shown. Figure 1 As shown, the flow of a belt fault detection method for a garment processing device provided in one embodiment of the present invention is as follows:

[0061] Step 102: Determine the first start time of the fluctuation cycle of the drum rotation based on the first fluctuation data of the motor operation;

[0062] Step 104: Record at least two initial start times to form the first time series;

[0063] Step 106: Based on the motor's electrical angle data, the number of motor pole pairs, and the set transmission ratio, estimate the second starting moment of the roller rotation fluctuation cycle;

[0064] Step 118: Record at least two second start times to form a second time series;

[0065] Step 110: Determine whether the belt is in a fault state based on the first time series and the second time series.

[0066] The present invention proposes a belt fault detection method for clothing processing equipment.

[0067] When the garment processing equipment is running, the clothes inside the drum will cause the drum to be unbalanced, meaning the load on the drum will usually be eccentric. As a result, the drum's rotation speed will fluctuate. Based on the combination of the motor's control function and the eccentric load, the first fluctuation data of the motor's operation will exhibit a periodicity. Since the drum is driven by the motor via a belt, the drum's fluctuation will be reflected in the motor's first fluctuation data according to the actual transmission ratio between the drum and the motor. In other words, the fluctuation period of the drum's rotation matches the first fluctuation data of the motor.

[0068] As shown above, based on the first fluctuation data during motor operation, the first starting moment of the fluctuation cycle of the drum rotation is determined. Due to the eccentricity of the load inside the drum, the drum rotation speed will form a sine or cosine waveform based on the effect of gravity. Therefore, each fluctuation cycle of the drum rotation has a first starting moment. The first starting moments of at least two fluctuation cycles are determined and recorded to form a first time series. The first time series can reflect the actual transmission ratio between the drum and the motor.

[0069] The electrical angle data of the motor is acquired. Based on the electrical angle data, the number of motor pole pairs, and the set transmission ratio, the second starting time of the roller rotation fluctuation cycle is estimated. Each estimated roller rotation fluctuation cycle has a second starting time. The second starting times of at least two fluctuation cycles are determined and recorded to form a second time series. Since the single-turn rotation of the motor is not affected by the actual transmission ratio, the roller rotation fluctuation cycle under reliable belt conditions can be estimated using the electrical angle data and the predetermined transmission ratio. Therefore, the second time series can serve as standard data reflecting the predetermined transmission ratio. The electrical angle data can be converted into the motor rotation angle using the number of motor pole pairs.

[0070] As shown above, by using the first time series and the second time series, the actual transmission ratio between the roller and the motor can be determined, and whether it meets the predetermined transmission ratio, thereby determining whether the current belt is in a fault state.

[0071] In other words, by collecting motor operating data, this invention can determine whether the belt is faulty, thereby enabling belt reliability testing and reducing the possibility of overall machine failure due to belt failure in garment processing equipment.

[0072] Among them, belt failures can include belt slippage, loosening, or jamming. Belt slippage, loosening, or jamming will cause changes in the transmission ratio between the roller and the motor, resulting in a difference between the actual transmission ratio and the preset transmission ratio. In other words, this invention utilizes the load eccentricity phenomenon that occurs when the clothing is unevenly distributed during operation of the clothing processing equipment, as well as the position estimation relationship of the control system itself, to quantitatively estimate the failure of belt slippage.

[0073] The belt fault detection method for clothing processing equipment provided by this invention first calculates the fluctuation period and fluctuation amount of the roller using the first fluctuation data of the motor, thereby obtaining the fluctuation period of the roller and its first start time. Using this point as a reference time, the first start time of subsequent fluctuation periods is continuously measured to obtain a first time sequence including indicators of the two first start times.

[0074] The first fluctuation data can be speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, or power input data, etc. Any physical quantity data that can reflect the load fluctuation of the drum can be used to calculate the first starting moment of the drum's fluctuation cycle.

[0075] Secondly, based on the motor's own angular position and the set transmission ratio, the second starting moment of the roller's oscillation cycle is estimated, and a second time series is established.

[0076] Finally, by comparing the first and second time series, and according to certain rules, it is determined whether the belt has experienced slippage or other faults.

[0077] In some embodiments, optionally, determining whether the belt is in a fault state based on a first time series and a second time series includes: comparing a first start time in the first time series with a second start time in the second time series of the same fluctuation period; and determining that the belt is in a fault state if a first difference between the first start time and the second start time is greater than or equal to a first threshold.

[0078] In this embodiment, determining whether the belt is in a fault state based on the first time series and the second time series includes: taking the first start time of a certain fluctuation period in the first time series, taking the second start time of the same fluctuation period in the second time series, subtracting the first start time and the second start time to obtain a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much larger than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, which can remind the user to repair or replace the belt, thereby reducing the impact of calculation error and detection error.

[0079] In some embodiments, optionally, comparing the first start time in the first time series of the same fluctuation period and the second start time in the second time series includes: when the motor is rotating at a constant speed, comparing the first start time in the first time series of the same fluctuation period and the second start time in the second time series; when the motor is rotating at an accelerated speed, comparing the first start time in the first time series of the fluctuation period when the speed drops back to the preset speed and the second start time in the second time series to determine whether the belt is in a fault state.

[0080] In this embodiment, comparing the first start time in the first time series with the second start time in the second time series of the same fluctuation period includes: when the motor is rotating at a constant speed, taking the first start time of a certain fluctuation period in the first time series, taking the second start time of the same fluctuation period in the second time series, subtracting the first start time from the second start time to obtain a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much greater than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, and reminding the user to repair or replace the belt.

[0081] When the motor is accelerating, the first and second starting times are recorded before the motor accelerates. After the motor completes the acceleration and the speed drops back to the preset speed, the first and second starting times are recorded again. When comparing, the first and second starting times after the speed drops back to the preset speed are compared. This can determine whether the belt drive is reliable when the motor is running at a high speed, and thus determine whether the belt is in a faulty state, thereby improving the reliability of belt fault diagnosis.

[0082] In some embodiments, optionally, determining the first start time of the fluctuation period of the drum rotation based on the first fluctuation data of the motor operation includes: determining the maximum fluctuation value of the rotation speed based on the first fluctuation data of the motor operation; adjusting the operating parameters of the motor when the maximum fluctuation value of the rotation speed is outside the preset fluctuation value range; and determining the first start time of the fluctuation period of the drum rotation based on the first fluctuation data when the maximum fluctuation value of the rotation speed is within the preset fluctuation value range.

[0083] In this embodiment, determining the first start time of the fluctuation cycle of the drum rotation based on the first fluctuation data of the motor operation includes: analyzing the first fluctuation data, extracting the maximum speed fluctuation value, and judging the maximum speed fluctuation value. If the maximum speed fluctuation value is outside the preset fluctuation value range, it indicates that the current load eccentricity of the drum is too large or too small, resulting in excessive or insufficient speed fluctuation, making it impossible to accurately determine the fluctuation cycle. In this case, the load eccentricity can be adjusted by adjusting the motor operating parameters until the maximum speed fluctuation value is within the maximum speed fluctuation value range. Once the maximum speed fluctuation value is within the preset fluctuation value range, the determination of the first start time can begin, thereby improving the accuracy and reliability of the determination of the first start time.

[0084] If the maximum speed fluctuation is greater than the upper limit of the preset fluctuation range, it indicates that the current roller load eccentricity is too large, resulting in excessive speed fluctuations that cannot be accurately determined by the fluctuation period. In this case, the load eccentricity can be reduced by adjusting the motor operating parameters. If the maximum speed fluctuation is less than the lower limit of the preset fluctuation range, it indicates that the current roller load eccentricity is too small, resulting in insufficient speed fluctuations that cannot be accurately determined by the fluctuation period. In this case, the load eccentricity can also be reduced by adjusting the motor operating parameters.

[0085] Specifically, the preset fluctuation value range can be less than or equal to the first preset fluctuation value, the preset fluctuation value range can be greater than or equal to the second preset fluctuation value, and the preset fluctuation value range can also be less than or equal to the third fluctuation threshold and greater than or equal to the fourth preset fluctuation value, wherein the third fluctuation threshold is greater than the fourth fluctuation threshold.

[0086] In some embodiments, optionally, when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, determining the first starting time of the fluctuation period of the drum rotation based on the first fluctuation data includes: when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, determining the average rotational speed of the drum rotation based on the first fluctuation data; when the data point of the first fluctuation data and the average rotational speed are equal, and the rotational speed shows an upward trend, recording the time corresponding to the data point as the first starting time.

[0087] In this embodiment, when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range, the first starting moment of the fluctuation period of the drum rotation is determined based on the first fluctuation data. This includes: when the maximum fluctuation value of the rotational speed is within the preset fluctuation value range, analyzing the first fluctuation data and determining the average rotational speed; if a certain data point of the first fluctuation data is equal to the average rotational speed, and the rotational speed at that data point shows an upward trend, the time corresponding to the data point is determined as the first starting moment, and this moment is recorded. Based on the characteristic of the load eccentricity inside the drum, when the drum rotates, its rotational speed changes from small to large and then from large to small. Therefore, by defining the position of the first starting moment in the above manner, the accuracy of determining the fluctuation period can be improved.

[0088] In some embodiments, optionally, estimating the second start time of the oscillation cycle of the drum rotation based on the electrical angle data of the motor, the number of motor pole pairs, and a set transmission ratio includes: calculating the electrical angle change of the motor based on the electrical angle data and the number of motor pole pairs; accumulating the electrical angle change to estimate the electrical angle change cycle that conforms to the oscillation cycle of the drum; determining that the electrical angle change cycle enters the next cycle when the electrical angle change cycle conforms to the set transmission ratio; and determining the second start time of the oscillation cycle of the drum rotation based on the electrical angle change cycle.

[0089] In this embodiment, estimating the second starting moment of the roller rotation fluctuation period based on the motor's electrical angle data, the number of motor pole pairs, and the set transmission ratio includes: calculating the change in the motor's electrical angle based on the motor's electrical angle data and the number of motor pole pairs. During the rotation of the motor, its electrical angle changes constantly. Combining this with the number of motor pole pairs, the change in electrical angle can be determined. The change in electrical angle reflects the number of rotations of the motor. When the belt drive is reliable, the number of rotations of the motor and the number of rotations of the roller should conform to the set transmission ratio of the belt. Therefore, the change in electrical angle that conforms to the roller's fluctuation period can be estimated by the change in electrical angle. In other words, the change in electrical angle is determined by accumulating the changes in electrical angle.

[0090] After confirming that the accumulated electrical angle change within the electrical angle change cycle meets the set transmission ratio, the electrical angle change cycle is determined to enter the next cycle, thus obtaining waveform data of one electrical angle change cycle. The starting time of the electrical angle change cycle is used as the second starting time, thereby improving the accuracy of the estimation of the roller's fluctuation cycle.

[0091] In some embodiments, the first start time and the second start time may be initialized simultaneously.

[0092] In this embodiment, the first start time and the second start time are initialized simultaneously, so that the first start time in the first time series and the second start time in the second time series correspond one-to-one, making it easier to compare the first start time and the second start time.

[0093] In some embodiments, the first fluctuation data may optionally be at least one of the following: speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data.

[0094] In this embodiment, the rotational speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data are all affected by the load inside the drum. Therefore, the oscillation period of the drum can be determined by analyzing the above data.

[0095] Specifically, the first fluctuation data will be used as the rotational speed data for explanation, such as... Figure 3 As shown in the figure, the control system when the motor drives the load is as follows: w* is the speed command, w is the motor speed, TL is the load torque, Te represents the motor electromagnetic torque, and - and + represent signal calculations, i.e., the torque caused by load eccentricity. When the clothes in the drum are evenly distributed, the clothes represent the load inertia of the motor. The inertia of these clothes and the inertia of the drum together represent the transfer function P(s), which can be simplified as an inertia and integral element P(s) = 1 / (J×s), where P(s) represents the transfer function of the inertia of the clothes and the inertia of the drum, J represents the load inertia, s represents the differentiation operation, and 1 / s represents the integration operation. The imbalance in the clothes can be described by a periodic eccentric load (e.g., Figure 8 The effect of the eccentric load on the speed control system of the motor can be expressed by TL=a×sin(θ), where TL represents the load torque, a represents the load amplitude, and θ represents the eccentric position. The load effect is theoretically a sine or cosine function, and its period is the mechanical period of the roller, that is, the fluctuation period.

[0096] C(s) is the transfer function of the motor speed control system. The simplest control method is the PI (Proportional-Integral) controller, that is, C(s) = Kp + Ki / s. C(s) represents the transfer function of the motor speed control system, Ki is the integral gain, Kp is the proportional gain, s represents the derivative operation, and 1 / s represents the integral operation.

[0097] The transfer function from the speed command w* to the speed w is Gw=C(s)×P(s) / (1+C(s)P(s))=(Kp×s+Ki) / (J×s)2 +Kp×s+Ki), where Gw represents the transfer function from speed command w* to speed w, C(s) represents the transfer function of the motor speed control system, Ki is the integral gain, Kp is the proportional gain, s represents the differential operation, P(s) represents the transfer function of the inertia of the clothes and the inertia of the drum, and J represents the inertia of the load.

[0098] The transfer function from load torque TL to speed due to load disturbance is GL=-P(s) / (1+C(s)P(s))=-s / (J×s) 2 +Kp×s+Ki). Where GL represents the transfer function from the load torque TL of the load disturbance to the speed, C(s) represents the transfer function of the motor speed control system, Ki is the integral gain, Kp is the proportional gain, s represents the differential operation, P(s) represents the transfer function of the inertia of the clothes and the inertia of the drum, and J represents the inertia of the load.

[0099] When the load torque TL is an interference that forms a sinusoidal wave shape as the mechanical angle of the drum changes, its corresponding effect on the drum speed is also in the form of a sinusoidal wave.

[0100] Since the diameters of the first pulley on the motor and the second pulley on the drum are related, it can be known that the rotational speed of the drum is proportional to the rotational speed of the motor, i.e., the rotational speed ratio is equal to the rotational speed ratio, i.e., nr = R / r, where nr represents the rotational speed ratio, R represents the radius of the second pulley, r represents the radius of the first pulley, and " / " represents "÷".

[0101] Therefore, the impact of the load inside the drum is reflected in the motor's speed and speed fluctuations, and the above conversion relationship also applies. That is, the effect of the load torque on the motor is TL / nr, where TL represents the load torque, nr represents the set transmission ratio, and the fluctuation period is w. g ×nr, where w g This indicates the oscillation period of the roller, nr represents the set transmission ratio, and " / " represents "÷".

[0102] In addition, the motor's speed data can be obtained from the motor's encoder.

[0103] In some embodiments, the acquisition period of the first fluctuation data may be calculated, and determined based on the control period of the motor's speed loop.

[0104] In this embodiment, the motor control system is controlled by an MCU (Micro Control Unit). Typically, a fixed algorithm is operated using a certain time period. For example, the typical control period of the current loop can be a first duration, and the control period of the speed loop can be a second duration. The value of the first duration can be from 50us to 200us, specifically, the value of the first duration can be 50us, 100us, 150us, or 200us. The value of the second duration can be from 300us to 500us, specifically, the value of the first duration can be 300us, 400us, or 500us.

[0105] Taking a speed loop control cycle of 400µs and the first fluctuation data as speed data as an example, the basic operation cycle for data acquisition is Ts, that is, the calculation of the first starting moment is performed every Ts interval. Each time a calculation cycle is added, its time label can be represented by an integer i. The physical quantities obtained in each calculation cycle are distinguished by (i). For example, if the motor speed data at the current moment is set as wm(i), then the speed data of the previous cycle is wm(i-1), and the speed data of the next cycle is wm(i+1). The value of i can be set to 0 at the beginning of the first fluctuation cycle for convenient calculation.

[0106] To facilitate calculation and judgment, i can be initialized to 0 at the first start of the first fluctuation cycle. Then, i = i + 1 is calculated for the next fluctuation cycle, thereby obtaining the first time series based on the period Ts interval.

[0107] In some embodiments, optionally, determining the first start time of the fluctuation period of the drum rotation based on the first fluctuation data of the motor operation includes: collecting the motor operation data; and filtering the operation data to obtain the first fluctuation data.

[0108] Figure 2 A second flowchart illustrates a belt fault detection method for a garment processing device according to an embodiment of the present invention. Figure 2 As shown, the flow of a belt fault detection method for a garment processing device provided in one embodiment of the present invention is as follows:

[0109] Step 202: The motor drives the roller to rotate, so that the clothes are stably attached to the inner wall of the roller. The motor speed wm is determined and the speed is filtered to obtain the filtered speed wf.

[0110] Step 204: Determine the oscillation period of the roller, and determine the average rotational speed wmavg and the maximum rotational speed oscillation value Δwmax of the roller.

[0111] Step 206: Determine whether Δwmax is within the preset fluctuation range; if Δwmax is outside the preset fluctuation range, proceed to step 208; if Δwmax is within the preset fluctuation range, proceed to step 210.

[0112] Step 208: Control the motor speed change or reverse, etc., to adjust the distribution of clothes and adjust the load eccentricity.

[0113] Step 210: Based on the first fluctuation data of the motor, calculate the first starting time of the fluctuation cycle of the drum and form the first time series.

[0114] Step 212: Estimate the second start time of the roller's oscillation cycle using the motor's electrical angle data, the number of motor pole pairs, and the set transmission ratio, and form the second time series.

[0115] Step 214: Compare the first time series and the second time series to determine whether the transmission error of the belt exceeds the first threshold, thereby determining whether the belt is slipping.

[0116] Specifically, taking the first fluctuation data as the speed data as an example, in each calculation, the motor speed data wm(i) is first obtained. This data can be obtained by position sensors such as encoders installed on the motor shaft, or estimated by Hall switches, or estimated by various algorithms in sensorless technology.

[0117] First, obtain the rotational speed data wm(i). The length of the data is greater than the fluctuation period of a cosine waveform, and then perform rolling updates.

[0118] The length n of the first time series should cover one oscillation cycle of the roller. For example, based on the motor speed data wm(i) (rpm) and the set transmission ratio nr (nr = radius R of the second pulley / radius r of the first pulley), and the period Ts (seconds), the roller speed can be obtained as wm(i) / nr (rpm), and the time of one oscillation cycle of the roller is approximately TsL = nr × 60 / wm(i) (seconds). The length n of the first time series is then TsL / Ts (units are dimensionless and rounded to the nearest integer), where " / " represents "÷". For ease of calculation, the length n of the first time series should cover the time TsL of the oscillation cycle, and can be approximately 1.1 times the time TsL of the oscillation cycle to ensure that the initial moment of the oscillation cycle can be stably obtained.

[0119] Next, filtering is performed. If necessary, the above data can be digitally filtered to eliminate high-frequency noise in the data.

[0120] For example: The data sequence of the above rotational speed wm(i) is [wm(1), wm(2), ..., wm(i), ..., wm(n)]. After low-pass filtering, the sequence of the first fluctuation data [wf(1), wf(2), ..., wf(i), ..., wf(n)] can be obtained. Considering the transition process of the filter, some early data is usually discarded and the later calculation is performed after the data stabilizes.

[0121] like Figure 4 and Figure 5 As shown, the average speed wfavg of the speed wf(i) is then calculated, and the belt fluctuation period is determined based on the maximum speed fluctuation value wferrmax. The average value wfavg = [wf(1) + wf(2) + ... + wf(n)] / n, where wf(1), wf(2), ..., wf(n) represent the peak and valley values ​​of multiple first fluctuation data, n represents the total amount of data, and " / " means "÷".

[0122] The maximum fluctuation value of the rotational speed is wferrmax = max(abs((wf(1)-wfavg), …(wf(n)-wfavg)), where max represents the maximum value, abs represents the absolute value function, and wfavg represents the average rotational speed.

[0123] The maximum speed fluctuation is proportional to the magnitude of the eccentric torque. Excessive eccentric torque will lead to control abnormalities, while insufficient eccentric torque will make it impossible to accurately determine the load cycle. Therefore, after calculating the maximum speed fluctuation, if the speed deviation meets the specified threshold, the first start time is determined. Otherwise, the first start time is not determined, or the eccentric load is reconstructed by methods such as acceleration and deceleration before calculating the maximum speed fluctuation and the average speed.

[0124] Calculate the point wf(i) that is closest to the average rotational speed wfavg, and based on the trend of the data before and after it, when the point is in an upward direction, define the moment of the point as the first start moment of the mechanical cycle of the drum eccentric torque.

[0125] At this moment, i is initialized and defined as i = 0. For the sake of convenience in calculation and explanation, it will only be initialized once in a belt slippage detection program.

[0126] This allows us to obtain the first start time of multiple fluctuation cycles, which can be recorded as [T0, T1, T2, T3, ...]. For example, the numerical characteristics of this time series can be [0, 100, 201, 299, ...], indicating that the first fluctuation cycle is 100Ts, and the second cycle is calculated to be 101Ts by subtracting 100 from 201. It is evident that the first start time and the fluctuation cycle interval can be obtained through the difference between the preceding and following data.

[0127] Next, let the electrical angle data of the motor be θe(i), where the electrical angle time is the absolute value of the electrical angle data of the motor, and its value range is 0-360°.

[0128] To simplify the explanation, this section only describes the direction of angle increase based on the direction of rotation; the direction of decrease can be calculated in the same way.

[0129] The relationship between the electrical angle variation period θesum(i) and the electrical angle data θe(i) is as follows:

[0130] For simplicity of calculation and explanation, i is synchronously initialized according to wf(i) above. At this time, θesum(i) = 0, i = 0; θe(i-1) = θe(i), θesum(i-1) = 0, i represents one fluctuation cycle, and i-1 represents the previous fluctuation cycle.

[0131] Then, in each calculation cycle Ts, the change in electrical angle Δθe(i) = θe(i) - θe(i-1) is calculated. If Δθe(i) < 0, it is determined that a cycle crossing from 360° has occurred, Δθe(i) = θe(i) - θe(i-1) + 360°.

[0132] θesum(i) = θesum(i-1) + Δθe(i) is used for normal cumulative calculation.

[0133] If θesum(i) - θe(0) ≥ R / r × Pp × 360°, then θesum(i) = θesum(i) - R / r × Pp × 360°. That is, subtracting R / r × Pp × 360° from θesum(i) and recording this as the current value of θesum(i) yields the following result: Figure 4 The waveform of θesum(i) is shown below, where R represents the radius of the second pulley, r represents the radius of the first pulley, Pp represents the number of pole pairs of the motor, and " / " represents "÷". The time at which the oscillation cycle of the drum is reached is recorded as the second starting time. Repeating the above algorithm yields the second time series of the drum's oscillation cycle estimated from the motor's electrical angle data. For example, the numerical values ​​of the starting time series [E0, E1, E2, ...] can be [0, 100, 200, 300, ...].

[0134] The first fluctuation sequence is the first time sequence [T0, T1, T2, T3, ...] of the first starting moment of the roller's fluctuation period, obtained from the motor's rotational speed data; the second fluctuation sequence is the second time sequence [E0, E1, E2, E3, ...] of the second starting moment of the roller's fluctuation period, obtained from the motor's rotational speed data.

[0135] Assuming the belt is functioning correctly, the first and second time series should be identical or very similar. Therefore, by comparing T3 and E3, we can determine whether belt slippage occurred between time T0 and T3. When slippage occurs, T3 > E3, and the amount of slippage is proportional to (T3 - E3). Based on this principle, in engineering practice, a certain calculation error can be considered, and by setting an appropriate threshold, the determination of whether belt slippage has occurred can be made. Alternatively, by comparing T3-T2 with E3-E2, we can determine whether belt slippage occurs within the third fluctuation cycle.

[0136] like Figure 4 As shown, when the motor is rotating at a constant speed, T1 and E1, T2 and E2, T3 and E3, etc. can be compared.

[0137] like Figure 5 As shown, when the motor is accelerating, T7 and E7, and T8 and E8 can be compared.

[0138] The methods described above can be implemented in various ways depending on specific features and / or example applications. For example, these methods can be implemented through a combination of hardware, firmware, and / or software. For instance, in a hardware implementation, the processor can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, electronic devices, other device units for performing the functions described above, and / or combinations thereof.

[0139] like Figure 6As shown, according to a second aspect of the present invention, the present invention provides a belt fault detection device 600 for a garment processing equipment, comprising: a first determining module 602, configured to determine a first starting moment of the fluctuation period of the roller rotation based on first fluctuation data of motor operation; a first recording module 604, configured to record at least two first starting moments to form a first time sequence; an estimation module 606, configured to estimate a second starting moment of the fluctuation period of the roller rotation based on the electrical angle data of the motor, the number of pole pairs of the motor, and a set transmission ratio; a second recording module 608, configured to record at least two second starting moments to form a second time sequence; and a second determining module 610, configured to determine whether the belt is in a fault state based on the first time sequence and the second time sequence.

[0140] The belt fault detection device for garment processing equipment provided by this invention addresses the issue that during operation, the garments inside the rollers can cause uneven weight distribution, resulting in eccentric loads and fluctuations in the roller's rotation speed. Based on the combination of the motor's control function and the eccentric load, the initial fluctuation data of the motor's operation exhibits a periodicity. Since the roller is driven by the motor via a belt, the roller's fluctuations are reflected in the motor's initial fluctuation data according to the actual transmission ratio between the roller and the motor. In other words, the roller's rotational fluctuation period matches the motor's initial fluctuation data.

[0141] As shown above, based on the first fluctuation data during motor operation, the first starting moment of the fluctuation cycle of the drum rotation is determined. Due to the eccentricity of the load inside the drum, the drum rotation speed will form a sine or cosine waveform based on the effect of gravity. Therefore, each fluctuation cycle of the drum rotation has a first starting moment. The first starting moments of at least two fluctuation cycles are determined and recorded to form a first time series. The first time series can reflect the actual transmission ratio between the drum and the motor.

[0142] The electrical angle data of the motor is acquired. Based on the electrical angle data, the number of motor pole pairs, and the set transmission ratio, the second starting time of the roller rotation fluctuation cycle is estimated. Each estimated roller rotation fluctuation cycle has a second starting time. The second starting times of at least two fluctuation cycles are determined and recorded to form a second time series. Since the single-turn rotation of the motor is not affected by the actual transmission ratio, the roller rotation fluctuation cycle under reliable belt conditions can be estimated using the electrical angle data and the predetermined transmission ratio. Therefore, the second time series can serve as standard data reflecting the predetermined transmission ratio. The electrical angle data can be converted into the motor rotation angle using the number of motor pole pairs.

[0143] As shown above, by using the first time series and the second time series, the actual transmission ratio between the roller and the motor can be determined, and whether it meets the predetermined transmission ratio, thereby determining whether the current belt is in a fault state.

[0144] In other words, by collecting motor operating data, this invention can determine whether the belt is faulty, thereby enabling belt reliability testing and reducing the possibility of overall machine failure due to belt failure in garment processing equipment.

[0145] In some embodiments, the second determining module optionally includes: a comparison submodule for comparing a first start time in a first time series with a second start time in a second time series of the same fluctuation period; and a first determining submodule for determining that the belt is in a fault state if the first difference between the first start time and the second start time is greater than or equal to a first threshold.

[0146] In this embodiment, the first start time of a certain fluctuation period is taken in the first time series, and the second start time of the same fluctuation period is taken in the second time series. The difference between the first start time and the second start time is obtained as a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much larger than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, which can remind the user to repair or replace the belt, thereby reducing the impact of calculation error and detection error.

[0147] In some embodiments, the comparison submodule may optionally include: a first comparison unit, configured to compare a first start time in a first time series with a second start time in a second time series when the motor is rotating at a constant speed; and a second comparison unit, configured to compare a first start time in a first time series with a second start time in a second time series when the motor is rotating at an accelerated speed, and to determine whether the belt is in a fault state.

[0148] In this embodiment, comparing the first start time in the first time series with the second start time in the second time series of the same fluctuation period includes: when the motor is rotating at a constant speed, taking the first start time of a certain fluctuation period in the first time series, taking the second start time of the same fluctuation period in the second time series, subtracting the first start time from the second start time to obtain a first difference value. If the first difference value is greater than or equal to a first threshold, that is, the fluctuation period of the roller is much greater than the estimated fluctuation period, it indicates that the current belt transmission reliability is low, thereby determining that the current belt is in a fault state, and reminding the user to repair or replace the belt.

[0149] When the motor is accelerating, the first and second starting times are recorded before the motor accelerates. After the motor completes the acceleration and the speed drops back to the preset speed, the first and second starting times are recorded again. When comparing, the first and second starting times after the speed drops back to the preset speed are compared. This can determine whether the belt drive is reliable when the motor is running at a high speed, and thus determine whether the belt is in a faulty state, thereby improving the reliability of belt fault diagnosis.

[0150] In some embodiments, the first determining module may optionally include: a second determining submodule, configured to determine the maximum speed fluctuation value based on the first fluctuation data of the motor operation; an adjusting submodule, configured to adjust the operating parameters of the motor when the maximum speed fluctuation value is outside a preset fluctuation value range; and a third determining submodule, configured to determine the first start time of the fluctuation cycle of the drum rotation based on the first fluctuation data when the maximum speed fluctuation value is within a preset fluctuation value range.

[0151] In some embodiments, the third determining submodule may optionally include: a first determining unit, configured to determine the average rotational speed of the drum based on the first fluctuation data when the maximum fluctuation value of the rotational speed is within a preset fluctuation value range; and a first recording unit, configured to record the time corresponding to the data point as the first starting time when the data point of the first fluctuation data is equal to the average rotational speed and the rotational speed shows an upward trend.

[0152] In some embodiments, optionally, the estimation module includes: a first calculation submodule, configured to calculate the electrical angle change of the motor based on electrical angle data and the number of motor pole pairs; an estimation submodule, configured to accumulate the electrical angle change to estimate the electrical angle change period that conforms to the oscillation period of the drum; a fourth determination submodule, configured to determine that the electrical angle change period enters the next cycle when the electrical angle change period conforms to a set transmission ratio; and a fifth determination submodule, configured to determine the second starting time of the oscillation period of the drum rotation based on the electrical angle change period.

[0153] In some embodiments, the first start time and the second start time may be initialized simultaneously.

[0154] In this embodiment, the first start time and the second start time are initialized simultaneously, so that the first start time in the first time series and the second start time in the second time series correspond one-to-one, making it easier to compare the first start time and the second start time.

[0155] In some embodiments, the first fluctuation data may optionally be at least one of the following: speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data.

[0156] In this embodiment, the rotational speed data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data are all affected by the load inside the drum. Therefore, the oscillation period of the drum can be determined by analyzing the above data.

[0157] like Figure 7 As shown, according to a third aspect of the present invention, the present invention provides a garment processing device 700, including a controller 702, the controller 702 being used to store and run programs or instructions, which, when executed, implement the steps of the belt fault detection method for the garment processing device provided in the first aspect embodiment.

[0158] The garment processing device provided by the present invention includes a program or instructions that, when executed by a controller, implement the belt fault detection method of the garment processing device as provided in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method of the garment processing device as provided in the first aspect embodiment, which will not be described in detail here.

[0159] like Figure 8 and Figure 9 As shown, the garment processing equipment includes a motor 810, a first pulley 820, a second pulley 830, a roller 840, a belt 850, and a support wheel 870. The first pulley 820 is mounted on the motor shaft 812 of the motor 810, the second pulley 830 is mounted on the roller 840, the belt 850 is mounted on the first pulley 820 and the second pulley 830, and the support wheel 870 supports the roller 840. The roller 840 can hold a load 860, which is garments.

[0160] According to a fourth aspect of the present invention, an electronic device is provided, including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the belt fault detection method for a clothing processing device as provided in the first aspect embodiment.

[0161] The electronic device provided by the present invention includes a program or instructions that, when executed by a processor, implement the belt fault detection method of the garment processing device as provided in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method of the garment processing device as provided in the first aspect embodiment, which will not be described in detail here.

[0162] According to a fifth aspect of the present invention, a storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the belt fault detection method for a garment processing device as provided in the first aspect embodiment.

[0163] The storage medium provided by the present invention stores a computer program that, when executed by a processor, implements the steps of the belt fault detection method for the garment processing equipment provided in the first aspect embodiment. Therefore, it has all the beneficial effects of the belt fault detection method for the garment processing equipment provided in the first aspect embodiment, which will not be described in detail here.

[0164] The program or instructions are stored in the controller's storage medium, which can be a tangible device that holds and stores instructions for use by the instruction execution device. Computer storage media can be, but is not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer storage media includes: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EROM, EPROM, or flash memory), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital video disc (DVD), memory cards, floppy disks, encoding devices (e.g., punched cards or grooves with raised structures for recording instructions), and any suitable combination of the foregoing. The computer storage medium used here should not be understood as the transmission signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media, or electrical signals transmitted through wires.

[0165] In this invention, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more unless otherwise explicitly defined. The terms "install," "connect," "link," and "fix" should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; "link" can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0166] In the description of this invention, it should be understood that the terms "upper", "lower", "left", "right", "front", "rear", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the components or units referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0167] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0168] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting belt failure in a garment processing device, characterized in that, include: Based on the first fluctuation data of the motor operation, determine the first starting moment of the fluctuation cycle of the drum rotation; Record at least two of the first start times to form a first time series; Based on the electrical angle data of the motor, the number of motor pole pairs, and the set transmission ratio, estimate the second starting moment of the fluctuation period of the drum rotation; Record at least two second start times to form a second time series; Based on the first time series and the second time series, determine whether the belt is in a fault state.

2. The belt fault detection method for clothing processing equipment according to claim 1, characterized in that, Determining whether the belt is in a fault state based on the first time series and the second time series includes: Compare the first start time in the first time series with the second start time in the second time series, which have the same fluctuation period; If the first difference between the first start time and the second start time is greater than or equal to a first threshold, the belt is determined to be in a fault state.

3. The belt fault detection method for clothing processing equipment according to claim 2, characterized in that, Comparing the first start time in the first time series and the second start time in the second time series within the same fluctuation period includes: When the motor is rotating at a constant speed, compare the first starting time in the first time series with the second starting time in the second time series, which have the same fluctuation period; When the motor is accelerating, the first starting moment in the first time series of the fluctuation period when the speed drops back to the preset speed and the second starting moment in the second time series are compared to determine whether the belt is in a fault state.

4. The belt fault detection method for clothing processing equipment according to any one of claims 1 to 3, characterized in that, Based on the initial fluctuation data of the motor operation, the first starting moment of the fluctuation cycle of the drum rotation is determined, including: Based on the first fluctuation data of the motor operation, determine the maximum fluctuation value of the rotational speed; If the maximum fluctuation value of the rotational speed is outside the preset fluctuation value range, adjust the operating parameters of the motor; When the maximum fluctuation value of the rotational speed is within the preset fluctuation value range, the first start time of the fluctuation period of the drum rotation is determined based on the first fluctuation data.

5. The belt fault detection method for clothing processing equipment according to claim 4, characterized in that, When the maximum fluctuation value of the rotational speed is within the preset fluctuation value range, the first start time of the fluctuation period of the drum rotation is determined based on the first fluctuation data, including: If the maximum fluctuation value of the rotational speed is within the preset fluctuation value range, the average rotational speed is determined based on the first fluctuation data; When the data point of the first fluctuation data is equal to the average rotational speed, and the rotational speed shows an upward trend, the time corresponding to the data point is recorded as the first starting time.

6. The belt fault detection method for clothing processing equipment according to any one of claims 1 to 3, characterized in that, Based on the electrical angle data of the motor, the number of pole pairs of the motor, and the set transmission ratio, the second starting moment of the fluctuation period of the drum rotation is estimated, including: Based on the electrical angle data and the number of motor pole pairs, calculate the change in electrical angle of the motor; The electrical angle changes are summed up to estimate the electrical angle change period that matches the oscillation period of the drum; If the electrical angle change cycle matches the set transmission ratio, the electrical angle change cycle is determined to enter the next cycle; The second starting time of the fluctuation period of the drum rotation is determined based on the electrical angle change period.

7. The belt fault detection method for clothing processing equipment according to any one of claims 1 to 3, characterized in that, The first start time and the second start time are initialized simultaneously.

8. The belt fault detection method for clothing processing equipment according to any one of claims 1 to 3, characterized in that, The first fluctuation data is at least one of the following: Speed ​​data, torque command data, torque estimation data, torque current command data, torque current detection data, power output data, and power input data.

9. A belt fault detection device for a garment processing equipment, characterized in that, include: The first determining module is used to determine the first starting moment of the fluctuation period of the drum rotation based on the first fluctuation data of the motor operation; The first recording module is used to record at least two first start times to form a first time series; The estimation module is used to estimate the second start time of the fluctuation period of the drum rotation based on the electrical angle data of the motor and the set transmission ratio; The second recording module is used to record at least two second start times to form a second time series; The second determining module is used to determine whether the belt is in a fault state based on the first time series and the second time series.

10. A garment processing device, characterized in that, The device includes a controller for storing and running programs or instructions that, when executed, implement the steps of the belt fault detection method for the garment processing equipment as described in any one of claims 1 to 8.

11. An electronic device, characterized in that, It includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of the belt fault detection method for the garment processing equipment as described in any one of claims 1 to 8.

12. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the belt fault detection method for the clothing processing equipment as described in any one of claims 1 to 8.

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